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Assessing the potential of sun-induced fluorescence and the canopy scattering coefficient to track large-scale vegetation dynamics in Amazon forests

Köhler, Philipp and Guanter, Luis and Kobayashi, Hideki and Walther, Sophia and Yang, Wei (2018) Assessing the potential of sun-induced fluorescence and the canopy scattering coefficient to track large-scale vegetation dynamics in Amazon forests. Remote Sensing of Environment, 204 . pp. 769-785. ISSN 0034-4257. doi:10.1016/j.rse.2017.09.025.

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Two new remote sensing vegetation parameters derived from spaceborne spectrometers and simulated with a three dimensional radiative transfer model have been evaluated in terms of their prospects and drawbacks for the monitoring of dense vegetation canopies: (i) sun-induced chlorophyll fluorescence (SIF), a unique signal emitted by photosynthetically active vegetation and (ii) the canopy scattering coefficient (CSC), a vegetation parameter derived along with the directional area scattering factor (DASF) and expected to be particularly sensitive to leaf optical properties. Here, we present the first global data set of DASF/CSC and examine the potential of CSC and SIF for providing complementary information on the controversially discussed vegetation seasonality in Amazon forests. A comparison between near-infrared SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument and the Orbiting Carbon Observatory-2 (OCO-2) (overpass time in the morning and noon, respectively) reveals the response of SIF to instantaneous photosynthetically active radiation (PAR). Large-scale seasonal swings of GOME-2 SIF amount up to 21% (regarding the annual maximum) and peak in October and around February, while OCO-2 SIF peaks in February. However, both time series agree very well if SIF is normalized by overpass time and wavelength. We further examine anistropic reflectance characteristics with the finding that the hot spot effect significantly impacts observed GOME-2 SIF values. On the contrary, our sensitivity analysis suggests that CSC is highly independent of sun-sensor geometry as well as atmospheric effects. The slight annual variability of CSC (3%) shows no clear seasonal cycle, while a relatively high spatial standard deviation points to a high degree of spatial heterogeneity in our study domain within the central Amazon Basin.

Item Type:Article
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URLURL TypeDescription
Köhler, Philipp0000-0002-7820-1318
Guanter, Luis0000-0002-8389-5764
Additional Information:© 2017 Elsevier Inc. Received 23 April 2016; Received in revised form 13 September 2017; Accepted 20 September 2017. Available online 05 October 2017. The research was funded by the Emmy Noether Programme of the German Research Foundation (GU 1276/1-1). Parts of this work were funded by the EARTH SCIENCE U.S. PARTICIPATING INVESTIGATOR (Grant Number: NNX15AH95G). Thanks to EUMETSAT to make the GOME-2 data available. The OCO-2 SIF data was produced by the OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center. With thanks to Alexa Oliphant and Troy S. Magney for their thoughtful linguistic revision of the manuscript.
Funding AgencyGrant Number
Deutsche Forschungsgemeinschaft (DFG)GU 1276/1-1
Subject Keywords:GOME-2; OCO-2; Sun-induced chlorophyll fluorescence; Concept of canopy spectral invariants; Canopy scattering coefficient; Directional area scattering factor; Amazon forest dynamics
Record Number:CaltechAUTHORS:20180111-101942484
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Official Citation:Philipp Köhler, Luis Guanter, Hideki Kobayashi, Sophia Walther, Wei Yang, Assessing the potential of sun-induced fluorescence and the canopy scattering coefficient to track large-scale vegetation dynamics in Amazon forests, Remote Sensing of Environment, Volume 204, January 2018, Pages 769-785, ISSN 0034-4257, (
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84252
Deposited By: Ruth Sustaita
Deposited On:11 Jan 2018 21:04
Last Modified:15 Nov 2021 20:18

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